Applied Probability by Kenneth Lange Hardcover Book

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Item specifics

Condition
Like New: A book in excellent condition. Cover is shiny and undamaged, and the dust jacket is ...
Book Title
Applied Probability
ISBN-13
9781071641712
ISBN
9781071641712
Category

About this product

Product Identifiers

Publisher
Springer
ISBN-10
1071641719
ISBN-13
9781071641712
eBay Product ID (ePID)
21070488560

Product Key Features

Number of Pages
Xvii, 602 Pages
Language
English
Publication Name
Applied Probability
Publication Year
2024
Subject
Numerical Analysis, Probability & Statistics / General, Computer Science
Type
Textbook
Subject Area
Mathematics, Computers
Author
Kenneth Lange
Series
Springer Texts in Statistics Ser.
Format
Hardcover

Dimensions

Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Edition Number
3
Dewey Edition
21
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
519.2
Table Of Content
Basic Notions of Probability Theory.- Calculation of Expectations.- Convexity, Optimization, and Inequalities.- Combinatorics.- Combinatorial Optimization.- Poisson Processes.- Discrete-Time Markov Chains.- Continuous-Time Markov Chains.- Branching Processes.- Martingales.- Diffusion Processes.- Asymptotic Methods.- Numerical Methods.- Poisson Approximation.- Number Theory.- Entropy.- Appendix: Mathematical Review.
Synopsis
Applied Probability presents a unique blend of theory and applications, with special emphasis on mathematical modeling, computational techniques, and examples from the biological sciences. Chapter 1 reviews elementary probability and provides a brief survey of relevant results from measure theory. Chapter 2 is an extended essay on calculating expectations. Chapter 3 deals with probabilistic applications of convexity, inequalities, and optimization theory. Chapters 4 and 5 touch on combinatorics and combinatorial optimization. Chapters 6 through 11 present core material on stochastic processes. If supplemented with appropriate sections from Chapters 1 and 2, there is sufficient material for a traditional semester-long course in stochastic processes covering the basics of Poisson processes, Markov chains, branching processes, martingales, and diffusion processes. This third edition includes new topics and many worked exercises. The new chapter on entropy stresses Shannon entropy and its mathematical applications. New sections in existing chapters explain the Chinese restaurant problem, the infinite alleles model, saddlepoint approximations, and recurrence relations. The extensive list of new problems pursues topics such as random graph theory omitted in the previous editions. Computational probability receives even greater emphasis than earlier. Some of the solved problems are coding exercises, and Julia code is provided. Mathematical scientists from a variety of backgrounds will find Applied Probability appealing as a reference. This updated edition can serve as a textbook for graduate students in applied mathematics, biostatistics, computational biology, computer science, physics, and statistics. Readers should have a working knowledge of multivariate calculus, linear algebra, ordinary differential equations, and elementary probability theory.
LC Classification Number
QA276-280

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